On-Device ML Engineer

Job Title : On-Device ML Engineer Lead & Build

Location : Rockville, MD (Hybrid)

Employment Type : Contract

Pay Range : $50 $70 / hour (based on experience)

About the Role

A federal project solutions provider is seeking a highly skilled On-Device ML Engineer to lead the design and development of advanced on-device machine learning solutions. In this role, you will build state-of-the-art ML systems optimized for edge and mobile environments, collaborate closely with engineering and data teams, and ensure adherence to strict data governance standards required in federal environments.

Key Responsibilities

Architect, build, and deploy ML models tailored for on-device inference using frameworks such as TensorFlow Lite, Core ML, or ONNX Runtime Mobile.

Lead technical development efforts and collaborate with cross-functional teams to deliver robust AI / ML systems for constrained devices.

Implement and optimize models for low-latency, privacy-focused, and offline-capable operation.

Maintain strong data governance, compliance, and security practices aligned with federal project standards.

Continuously evaluate and improve model accuracy, performance, and resource utilization on target hardware.

Document system architecture, model development processes, and deployment workflows.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

5+ years of professional experience in AI / ML development, with hands-on experience deploying ML models on edge or mobile devices.

Proficiency in Python or R , with strong understanding of ML pipelines and model optimization.

Experience with quantization, pruning, model compression, and hardware-aware ML techniques.

Strong communication skills and ability to collaborate effectively with technical and non-technical teams.

Preferred Qualifications

Experience working on federal or highly regulated projects.

Familiarity with GenAI / LLMs adapted for on-device execution.

Background in embedded systems, mobile development, or hardware-accelerated ML.

Why Join

Lead impactful on-device AI initiatives supporting federal programs.

Work in a collaborative hybrid environment with modern tools and technologies.

Competitive hourly compensation based on experience.